Big Data solutions enable enterprise system operators to explore new opportunities for data processing, storage and analytics at a scale and cost that was previously prohibitive. Emerging technologies now exist that enable enterprise system operators to exploit hybrid configurations, whereby data is split between new processing backends such as Big Data solutions and “traditional” enterprise data stores such as RDBMSs. In hybrid configurations, the traditional data store becomes a processing frontend and may either read data that resides in the processing backend cluster or write (offload) data to the processing backend while requiring continued read access to the relocated data. Hybrid configurations must achieve good performance, however, so it is critical that access to data that resides in the processing backend is made available as efficient as possible when being accessed by the processing frontend.